Quick look
## Observations: 160
## Variables: 40
## $ ID <chr> "j1", "j10", "j11", "j12", "j17", "j18", "j19...
## $ Site <chr> "u1", "u1", "u1", "u1", "u1", "u1", "u1", "u1...
## $ Group <chr> "p", "t", "p", "t", "t", "t", "t", "p", "t", ...
## $ Sex <chr> "female", "male", "female", "female", "female...
## $ Fatigue_BL <dbl> 5, 9, 8, 8, 7, NA, 7, 7, 7, 6, NA, NA, 8, 7, ...
## $ Fatigue_Wk4 <dbl> NA, 9, 8, NA, NA, NA, 9, NA, 7, 8, NA, NA, NA...
## $ Fatigue_Wk8 <dbl> NA, 9, 10, 8, NA, NA, 9, 8, 7, 8, NA, NA, NA,...
## $ Fatigue_Wk12 <dbl> NA, 10, 7, 8, 5, NA, NA, NA, 7, 8, NA, NA, NA...
## $ Fatigue_Wk24 <dbl> NA, 10, NA, 8, NA, NA, NA, 6, 8, 8, NA, NA, N...
## $ Fatigue_Wk48 <dbl> NA, 7, NA, 6, NA, NA, NA, 8, NA, 9, NA, NA, N...
## $ Discomf_BL <dbl> 5, 9, 10, 8, 8, NA, 7, 6, 6, 6, NA, NA, 9, 9,...
## $ Discomf_Wk4 <dbl> NA, 9, 10, NA, NA, NA, 9, NA, 7, 8, NA, NA, N...
## $ Discomf_Wk8 <dbl> NA, 9, 10, 9, NA, NA, 9, 8, 7, 8, NA, NA, NA,...
## $ Discomf_Wk12 <dbl> NA, 10, 10, 9, 5, NA, NA, NA, 9, 8, NA, NA, N...
## $ Discomf_Wk24 <dbl> NA, 10, NA, 8, NA, NA, NA, 7, 8, 8, NA, NA, N...
## $ Discomf_Wk48 <dbl> NA, 8, NA, 8, NA, NA, NA, 8, NA, 9, NA, NA, N...
## $ Distress_BL <dbl> 5, 10, 10, 9, 10, NA, 9, 9, 5, 8, NA, NA, 9, ...
## $ Distress_Wk4 <dbl> NA, 9, 10, NA, NA, NA, 10, NA, 9, 9, NA, NA, ...
## $ Distress_Wk8 <dbl> NA, 9, 10, 9, NA, NA, 9, 7, 7, 8, NA, NA, NA,...
## $ Distress_Wk12 <dbl> NA, 10, 8, 9, 6, NA, NA, NA, 9, 9, NA, NA, NA...
## $ Distress_Wk24 <dbl> NA, 10, NA, 8, NA, NA, NA, 8, 9, 9, NA, NA, N...
## $ Distress_Wk48 <dbl> NA, 8, NA, 7, NA, NA, NA, 8, NA, 9, NA, NA, N...
## $ Other_sympt_BL <dbl> 1, 10, 10, 9, 10, NA, 8, 9, 7, 8, NA, NA, NA,...
## $ Other_sympt_Wk4 <dbl> NA, 9, 10, NA, NA, NA, 10, NA, 9, 9, NA, NA, ...
## $ Other_sympt_Wk8 <dbl> NA, 9, 10, 9, NA, NA, 9, 8, 8, 10, NA, NA, NA...
## $ Other_sympt_Wk12 <dbl> NA, 10, 10, 10, 5, NA, NA, NA, 10, 9, NA, NA,...
## $ Other_sympt_Wk24 <dbl> NA, 10, NA, 9, NA, NA, NA, 8, 9, 9, NA, NA, N...
## $ Other_sympt_Wk48 <dbl> NA, 8, NA, 8, NA, NA, NA, 8, NA, 9, NA, NA, N...
## $ Tasks_BL <dbl> 5, 10, 10, 10, 9, NA, 10, 8, 7, 8, NA, NA, 9,...
## $ Tasks_Wk4 <dbl> NA, 10, 10, NA, NA, NA, 10, NA, 10, 9, NA, NA...
## $ Tasks_Wk8 <dbl> NA, 10, 10, 10, NA, NA, 10, 8, 9, 10, NA, NA,...
## $ Tasks_Wk12 <dbl> NA, 10, 10, 10, 4, NA, NA, NA, 10, 9, NA, NA,...
## $ Tasks_Wk24 <dbl> NA, 10, NA, 9, NA, NA, NA, 9, 10, 10, NA, NA,...
## $ Tasks_Wk48 <dbl> NA, 8, NA, 9, NA, NA, NA, 8, NA, 9, NA, NA, N...
## $ Non_drug_BL <dbl> 5, 10, 10, 10, 9, NA, 10, 8, 7, 9, NA, NA, 10...
## $ Non_drug_Wk4 <dbl> NA, 10, 10, NA, NA, NA, 10, NA, 10, 9, NA, NA...
## $ Non_drug_Wk8 <dbl> NA, 10, 10, 10, NA, NA, 10, 8, 9, 10, NA, NA,...
## $ Non_drug_Wk12 <dbl> NA, 10, 10, 10, 5, NA, NA, NA, 10, 9, NA, NA,...
## $ Non_drug_Wk24 <dbl> NA, 10, NA, 10, NA, NA, NA, 9, 10, 10, NA, NA...
## $ Non_drug_Wk48 <dbl> NA, 6, NA, 9, NA, NA, NA, 8, NA, 7, NA, NA, N...
Clean data
# Calculate mean score for each time point
se6_BL <- se6 %>% select(contains('BL'))
se6$mean_BL <- rowMeans(se6_BL, na.rm = TRUE)
se6_Wk4 <- se6 %>% select(contains('Wk4'))
se6$mean_Wk4 <- rowMeans(se6_Wk4, na.rm = TRUE)
se6_Wk8 <- se6 %>% select(contains('Wk8'))
se6$mean_Wk8 <- rowMeans(se6_Wk8, na.rm = TRUE)
se6_Wk12 <- se6 %>% select(contains('Wk12'))
se6$mean_Wk12 <- rowMeans(se6_Wk12, na.rm = TRUE)
se6_Wk24 <- se6 %>% select(contains('Wk24'))
se6$mean_Wk24 <- rowMeans(se6_Wk24, na.rm = TRUE)
se6_Wk48 <- se6 %>% select(contains('Wk48'))
se6$mean_Wk48 <- rowMeans(se6_Wk48, na.rm = TRUE)
# Check
glimpse(se6)
## Observations: 160
## Variables: 46
## $ ID <chr> "j1", "j10", "j11", "j12", "j17", "j18", "j19...
## $ Site <chr> "u1", "u1", "u1", "u1", "u1", "u1", "u1", "u1...
## $ Group <chr> "p", "t", "p", "t", "t", "t", "t", "p", "t", ...
## $ Sex <chr> "female", "male", "female", "female", "female...
## $ Fatigue_BL <dbl> 5, 9, 8, 8, 7, NA, 7, 7, 7, 6, NA, NA, 8, 7, ...
## $ Fatigue_Wk4 <dbl> NA, 9, 8, NA, NA, NA, 9, NA, 7, 8, NA, NA, NA...
## $ Fatigue_Wk8 <dbl> NA, 9, 10, 8, NA, NA, 9, 8, 7, 8, NA, NA, NA,...
## $ Fatigue_Wk12 <dbl> NA, 10, 7, 8, 5, NA, NA, NA, 7, 8, NA, NA, NA...
## $ Fatigue_Wk24 <dbl> NA, 10, NA, 8, NA, NA, NA, 6, 8, 8, NA, NA, N...
## $ Fatigue_Wk48 <dbl> NA, 7, NA, 6, NA, NA, NA, 8, NA, 9, NA, NA, N...
## $ Discomf_BL <dbl> 5, 9, 10, 8, 8, NA, 7, 6, 6, 6, NA, NA, 9, 9,...
## $ Discomf_Wk4 <dbl> NA, 9, 10, NA, NA, NA, 9, NA, 7, 8, NA, NA, N...
## $ Discomf_Wk8 <dbl> NA, 9, 10, 9, NA, NA, 9, 8, 7, 8, NA, NA, NA,...
## $ Discomf_Wk12 <dbl> NA, 10, 10, 9, 5, NA, NA, NA, 9, 8, NA, NA, N...
## $ Discomf_Wk24 <dbl> NA, 10, NA, 8, NA, NA, NA, 7, 8, 8, NA, NA, N...
## $ Discomf_Wk48 <dbl> NA, 8, NA, 8, NA, NA, NA, 8, NA, 9, NA, NA, N...
## $ Distress_BL <dbl> 5, 10, 10, 9, 10, NA, 9, 9, 5, 8, NA, NA, 9, ...
## $ Distress_Wk4 <dbl> NA, 9, 10, NA, NA, NA, 10, NA, 9, 9, NA, NA, ...
## $ Distress_Wk8 <dbl> NA, 9, 10, 9, NA, NA, 9, 7, 7, 8, NA, NA, NA,...
## $ Distress_Wk12 <dbl> NA, 10, 8, 9, 6, NA, NA, NA, 9, 9, NA, NA, NA...
## $ Distress_Wk24 <dbl> NA, 10, NA, 8, NA, NA, NA, 8, 9, 9, NA, NA, N...
## $ Distress_Wk48 <dbl> NA, 8, NA, 7, NA, NA, NA, 8, NA, 9, NA, NA, N...
## $ Other_sympt_BL <dbl> 1, 10, 10, 9, 10, NA, 8, 9, 7, 8, NA, NA, NA,...
## $ Other_sympt_Wk4 <dbl> NA, 9, 10, NA, NA, NA, 10, NA, 9, 9, NA, NA, ...
## $ Other_sympt_Wk8 <dbl> NA, 9, 10, 9, NA, NA, 9, 8, 8, 10, NA, NA, NA...
## $ Other_sympt_Wk12 <dbl> NA, 10, 10, 10, 5, NA, NA, NA, 10, 9, NA, NA,...
## $ Other_sympt_Wk24 <dbl> NA, 10, NA, 9, NA, NA, NA, 8, 9, 9, NA, NA, N...
## $ Other_sympt_Wk48 <dbl> NA, 8, NA, 8, NA, NA, NA, 8, NA, 9, NA, NA, N...
## $ Tasks_BL <dbl> 5, 10, 10, 10, 9, NA, 10, 8, 7, 8, NA, NA, 9,...
## $ Tasks_Wk4 <dbl> NA, 10, 10, NA, NA, NA, 10, NA, 10, 9, NA, NA...
## $ Tasks_Wk8 <dbl> NA, 10, 10, 10, NA, NA, 10, 8, 9, 10, NA, NA,...
## $ Tasks_Wk12 <dbl> NA, 10, 10, 10, 4, NA, NA, NA, 10, 9, NA, NA,...
## $ Tasks_Wk24 <dbl> NA, 10, NA, 9, NA, NA, NA, 9, 10, 10, NA, NA,...
## $ Tasks_Wk48 <dbl> NA, 8, NA, 9, NA, NA, NA, 8, NA, 9, NA, NA, N...
## $ Non_drug_BL <dbl> 5, 10, 10, 10, 9, NA, 10, 8, 7, 9, NA, NA, 10...
## $ Non_drug_Wk4 <dbl> NA, 10, 10, NA, NA, NA, 10, NA, 10, 9, NA, NA...
## $ Non_drug_Wk8 <dbl> NA, 10, 10, 10, NA, NA, 10, 8, 9, 10, NA, NA,...
## $ Non_drug_Wk12 <dbl> NA, 10, 10, 10, 5, NA, NA, NA, 10, 9, NA, NA,...
## $ Non_drug_Wk24 <dbl> NA, 10, NA, 10, NA, NA, NA, 9, 10, 10, NA, NA...
## $ Non_drug_Wk48 <dbl> NA, 6, NA, 9, NA, NA, NA, 8, NA, 7, NA, NA, N...
## $ mean_BL <dbl> 4.333333, 9.666667, 9.666667, 9.000000, 8.833...
## $ mean_Wk4 <dbl> NaN, 8.416667, 9.666667, 7.833333, NaN, NaN, ...
## $ mean_Wk8 <dbl> NaN, 9.333333, 10.000000, 9.166667, NaN, NaN,...
## $ mean_Wk12 <dbl> NaN, 10.000000, 9.166667, 9.333333, 5.000000,...
## $ mean_Wk24 <dbl> NaN, 10.000000, NaN, 8.666667, NaN, NaN, NaN,...
## $ mean_Wk48 <dbl> NaN, 7.500000, NaN, 7.833333, NaN, NaN, NaN, ...
# Gather from wide format into long format
se6_tot <- se6 %>%
tidyr::gather(key = se6_question,
value = se6_rating,
-ID, - Site, - Group, -Sex)
# Create columns for domain and time
se6_tot <- se6_tot %>%
mutate(Domain = case_when(
stringr::str_detect(.$se6_question, "Fatigue") ~ "Fatigue",
stringr::str_detect(.$se6_question, "Discomf") ~ "Discomf",
stringr::str_detect(.$se6_question, "Distress") ~ "Distress",
stringr::str_detect(.$se6_question, "Other_sympt") ~ "Other_sympt",
stringr::str_detect(.$se6_question, "Tasks") ~ "Tasks",
stringr::str_detect(.$se6_question, "Non_drug") ~ "Non_drug",
stringr::str_detect(.$se6_question, "mean") ~ "Mean"
))
se6_tot <- se6_tot %>%
mutate(Week = case_when(
stringr::str_detect(.$se6_question, "Wk48") ~ 48,
stringr::str_detect(.$se6_question, "BL") ~ 0,
stringr::str_detect(.$se6_question, "Wk4$") ~ 4,
stringr::str_detect(.$se6_question, "Wk8") ~ 8,
stringr::str_detect(.$se6_question, "Wk12") ~ 12,
stringr::str_detect(.$se6_question, "Wk24") ~ 24
))
# Check column contents
unique(se6_tot$Week)
## [1] 0 4 8 12 24 48
## [1] "Fatigue" "Discomf" "Distress" "Other_sympt" "Tasks"
## [6] "Non_drug" "Mean"
# Delete time_point column
se6_tot <- se6_tot %>% select(-se6_question)